The \({\mathcal {G}}^0\) distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degrees of texture accurately. It is indexed by three parameters: the number of looks (which can be estimated for the whole image), a scale parameter and a texture parameter. This paper presents a new proposal for comparing samples from the \({\mathcal {G}}^0\) distribution using a geodesic distance (GD) as a measure of dissimilarity between models. The objective is quantifying the difference between pairs of samples from SAR data using both local parameters (scale and texture) of the \({\mathcal {G}}^0\) distribution. We propose three tests based on the GD which combine the tests presented in Naranjo-Torres et al. (IEEE J Sel Top Appl Earth Obs Remote Sens 10(3):987–997, 2017), and we estimate their probability distributions using permutation methods.

中文翻译：

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使用测地距离比较$$ {\ mathcal {G}} ^ 0 $$ G0分布中的样本

的\（{\ mathcal {G}} ^ 0 \）分布被广泛地用于monopolarized SAR图像的建模，因为它可以有不同程度的织构的准确表征区域。它由三个参数索引：外观数（可以对整个图像进行估计），比例参数和纹理参数。本文提出了一种新建议，即使用测地距离（GD）来比较\（{\ mathcal {G}} ^ 0 \）分布中的样本，以衡量模型之间的不相似性。目的是使用\（{\ mathcal {G}} ^ 0 \）的两个局部参数（比例和纹理）来量化来自SAR数据的样本对之间的差异。分配。我们建议基于GD的三个测试，结合Naranjo-Torres等人提出的测试。（IEEE J Sel顶级应用地球观测遥感10（3）：987-997，2017年），我们使用置换方法估算了它们的概率分布。